FED-HARGPT: A Hybrid Centralized-Federated Approach of a Transformer-based Architecture for Human Context Recognition

Researchers developed FED-HARGPT, a hybrid centralized-federated approach using Transformer architecture for Human Activity Recognition (HAR) with mobile sensor data. The study demonstrates that federated learning can achieve comparable performance to centralized models while preserving data privacy through the Flower framework.